Hierarchical Clustering for Adaptive Refactorings Identification

被引:0
|
作者
Czibula, Istvan Gergely [1 ]
Czibula, Gabriela [1 ]
机构
[1] Babes Bolyai Univ, Cluj Napoca, Romania
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper studies an adaptive refactoring problem. It is well-known that improving the software systems design through refactoring is one of the most important issues during the evolution of object oriented software systems. We focus on identifying the refactorings needed in order to improve the class structure of a software systems, in an adaptive manner, when new application classes are added to the system. We propose an adaptive clustering method based on an hierarchical agglomerative approach, that adjusts the structure of the system that was established by applying a hierarchical agglomerative clustering algorithm before the application classes set changed. The adaptive method identifies, more efficiently, the refactorings that would improve the structure of the extended software system, without decreasing the accuracy of the obtained results. An experiment testing the method's efficiency is also reported.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Refactorings Detection Using Hierarchical Clustering
    Czibula, Istvan Gergely
    Czibula, Gabriela
    PROCEEDINGS OF THE 2ND EUROPEAN COMPUTING CONFERENCE: NEW ASPECTS ON COMPUTERS RESEACH, 2008, : 332 - +
  • [2] Clustering Based Automatic Refactorings Identification
    Czibula, Istvan Gergely
    Czibula, Gabriela
    PROCEEDINGS OF THE 10TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING, 2009, : 253 - 256
  • [3] Hierarchical adaptive clustering
    Serban, Gabriela
    Campan, Alina
    INFORMATICA, 2008, 19 (01) : 101 - 112
  • [4] ADAPTIVE HIERARCHICAL CLUSTERING SCHEMES
    ROHLF, FJ
    SYSTEMATIC ZOOLOGY, 1970, 19 (01): : 58 - &
  • [5] Scalable adaptive hierarchical clustering
    Mathy, L
    Canonico, R
    Simpson, S
    Hutchison, D
    IEEE COMMUNICATIONS LETTERS, 2002, 6 (03) : 117 - 119
  • [6] An adaptive parallel hierarchical clustering algorithm
    Li, Zhaopeng
    Li, Kenli
    Xiao, Degui
    Yang, Lei
    HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS, PROCEEDINGS, 2007, 4782 : 97 - 107
  • [7] Adaptive Hierarchical Clustering Using Ordinal Queries
    Emamjomeh-Zadeh, Ehsan
    Kempe, David
    SODA'18: PROCEEDINGS OF THE TWENTY-NINTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, 2018, : 415 - 429
  • [8] Supervised Hierarchical Clustering in Fuzzy Model Identification
    Hartmann, Benjamin
    Baenfer, Oliver
    Nelles, Oliver
    Sodja, Anton
    Teslic, Luka
    Skrjanc, Igor
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2011, 19 (06) : 1163 - 1176
  • [9] Automatic identification of the number of clusters in hierarchical clustering
    Karna, Ashutosh
    Gibert, Karina
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (01): : 119 - 134
  • [10] Automatic identification of the number of clusters in hierarchical clustering
    Ashutosh Karna
    Karina Gibert
    Neural Computing and Applications, 2022, 34 : 119 - 134